Discovery Early Career Researcher Award - Grant ID: DE200100063
Funder
Australian Research Council
Funding Amount
$394,398.00
Summary
Nonmonotone Algorithms in Operator Splitting, Optimisation and Data Science. This project aims to develop the mathematical foundations for the analysis and development of optimisation algorithms used in data science. Despite their now ubiquitous use, machine learning software packages routinely rely on a number of algorithms from mathematical optimisation which are not properly understood. By moving beyond the traditional realms of Fejér monotone algorithms, this project expects to develop the m ....Nonmonotone Algorithms in Operator Splitting, Optimisation and Data Science. This project aims to develop the mathematical foundations for the analysis and development of optimisation algorithms used in data science. Despite their now ubiquitous use, machine learning software packages routinely rely on a number of algorithms from mathematical optimisation which are not properly understood. By moving beyond the traditional realms of Fejér monotone algorithms, this project expects to develop the mathematical theory required to rigorously justify the use of such algorithms and thereby ensure the integrity of the decision tools they produce. This mathematical framework is also expected to produce new algorithms for optimisation which benefit consumers of data science such as the health-care and cybersecurity sectors.Read moreRead less
Pattern Recognition and Interpretation in Sequence Data. With the recent advances in sequencing technology, the amount of biological sequence data available has increased tremendously. Extraction of knowledge from such data has lagged behind, awaiting the development of new automated methods for extracting meaning from the sequences. This project aims to develop fast and flexible algorithms for discovery of patterns in DNA and protein sequence data and to find families of sequences that share si ....Pattern Recognition and Interpretation in Sequence Data. With the recent advances in sequencing technology, the amount of biological sequence data available has increased tremendously. Extraction of knowledge from such data has lagged behind, awaiting the development of new automated methods for extracting meaning from the sequences. This project aims to develop fast and flexible algorithms for discovery of patterns in DNA and protein sequence data and to find families of sequences that share similar patterns. Association of these patterns with features of 3-dimensional structures of protein families and their functional characteristics can contribute towards the understanding of the relationship between primary structure and function of a protein.Read moreRead less
Engineering evolving complex network systems through structure intervention. This project aims to create a theory and technology for engineering complex network systems (CSS) through structural intervention. Complex network systems with evolving components are ubiquitous in nature and society. The science of biological networks, the Internet and large-scale power networks demand tools to understand and influence their evolving dynamics. This project could result in a breakthrough theory in netwo ....Engineering evolving complex network systems through structure intervention. This project aims to create a theory and technology for engineering complex network systems (CSS) through structural intervention. Complex network systems with evolving components are ubiquitous in nature and society. The science of biological networks, the Internet and large-scale power networks demand tools to understand and influence their evolving dynamics. This project could result in a breakthrough theory in network science and technology to augment biological systems and power grids. Expected benefits include cost-effective augmentation of power networks injected with renewable energy sources, and advancing basic biology research.Read moreRead less
Energy efficient sensing, computing and communication. This research will study trade-offs in resource use: bandwidth, power, and computational capacity of systems of sensors such as cameras, radars, and distributed sensor networks based on a statistical mechanical theory of information processing, leading to practical algorithms to optimize resource use in the design of such systems.